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The era of AI in the data warehouse is here — and Snowflake’s Cortex makes it easier than ever to bring Large Language Model (LLM) capabilities directly to your data without moving it outside the Snowflake ecosystem.
In this blog, I want to share how I built a Streamlit-powered AI App that encapsulates all the key Cortex LLM functions into a single, easy-to-use interface. This project started as a proof-of-concept (POC) for learning, but it quickly showcased how Cortex can become a powerful AI assistant within Snowflake for real-world business use cases.
Why This Matters
Most teams exploring AI in analytics face two challenges:
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Scattered Capabilities – Using different scripts or services for summarization, sentiment analysis, document parsing, or translation.
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Complex Integrations – Stitching together APIs, connectors, and pipelines outside the warehouse.
With Snowflake Cortex, all these capabilities are natively available inside Snowflake — and with Streamlit (already integrated in Snowsight), you can package them into an interactive AI workspace in minutes.
What we Built: Cortex LLM Studio
I created a unified Cortex AI Studio App with a sidebar navigation that allows users to switch between multiple LLM-powered functions:
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Summarize Text – Instantly shorten transcripts or documents into crisp summaries.
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Translate Text – Translate across multiple languages with just a click.
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Sentiment Analysis – Gauge customer feedback sentiment in real time.
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Parse Document – Extract structured text from files stored in a Snowflake stage.
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Classify Text – Categorize text into business domains (e.g., Tech, Finance, Sports).
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Extract Answer – Ask targeted questions against a block of text.
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Complete Prompt – Generate responses using pre-trained models like llama3, mistral, and jamba.
All these are powered by Snowflake Cortex functions such as SUMMARIZE, TRANSLATE, SENTIMENT, CLASSIFY_TEXT, EXTRACT_ANSWER, PARSE_DOCUMENT, and COMPLETE.
The USP of This POC
What makes this project stand out?
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One App, Many Functions – Instead of running SQL manually, all Cortex capabilities are consolidated into a single Streamlit interface.
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Business-Ready Demos – Examples like call transcript summarization, health record parsing, and market news classification show direct applicability.
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Snowflake-Native – No external APIs, no extra infrastructure. Everything runs securely within Snowflake.
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User-Friendly Design – Clean UI with tabs, icons, and download options makes this more than just a tech demo — it feels like a mini AI product.
I’ll be sharing a demo video on LinkedIn showing this app in action — walking through summarization, translation, classification, and more, all from a single screen.
This POC is just the beginning. Imagine extending it with task orchestration, alerts, or Cortex Search for semantic document lookup. That’s the vision — Snowflake Cortex as your AI Co-pilot, not just a set of isolated functions.
